The Panel on Alternative Liquid Transportation Fuels developed a model to simulate the capital and operating costs and the carbon emissions of ethanol plants. The model simulations were used to compare process economics and environmental effects in different scenarios of technological developments and improved efficiencies, with different feedstocks, and in ethanol plants of various sizes. SuperPro Designer®, chemical-process simulation software, was used by the panel to run the model simulations because it contains a set of unit procedures that can be customized to the specific modeling needs of the corn grain-to-ethanol and cellulosic biomass-to-ethanol processes. It was also used in another study (Kwiatkowski et al., 2005). The software includes a well-developed economic-evaluation package with such parameters as financing, depreciation, running royalty expenses, inflation rate, and taxes. This appendix will first discuss the composition of different biomass feedstocks, then the ethanol-plant simulation models that the panel used, and finally an example of an economic analysis generated by SuperPro Designer.

BIOMASS COMPOSITION

Feedstock Description: Poplar and High-Sugar/Glucan Biomass

Poplar woodchips were used as biomass feedstock for all initial analyses. Composition was obtained from M. Ladisch and colleagues (Purdue University) and is summarized in Table I.1. “Wet” woodchips, which are unprocessed as provided by the forestry-products industry as by-products, were used in the analyses. They

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I Modeling of Capital and Operating Costs
and Carbon Emissions of Ethanol Plants with
SuperPro Designer®
T
he Panel on Alternative Liquid Transportation Fuels developed a model
to simulate the capital and operating costs and the carbon emissions of
ethanol plants. The model simulations were used to compare process eco-
nomics and environmental effects in different scenarios of technological develop-
ments and improved efficiencies, with different feedstocks, and in ethanol plants
of various sizes. SuperPro Designer®, chemical-process simulation software, was
used by the panel to run the model simulations because it contains a set of unit
procedures that can be customized to the specific modeling needs of the corn
grain-to-ethanol and cellulosic biomass-to-ethanol processes. It was also used in
another study (Kwiatkowski et al., 2005). The software includes a well-developed
economic-evaluation package with such parameters as financing, depreciation,
running royalty expenses, inflation rate, and taxes. This appendix will first discuss
the composition of different biomass feedstocks, then the ethanol-plant simulation
models that the panel used, and finally an example of an economic analysis gener-
ated by SuperPro Designer.
BIOMASS COMPOSITION
Feedstock Description: Poplar and High-Sugar/Glucan Biomass
Poplar woodchips were used as biomass feedstock for all initial analyses. Com-
position was obtained from M. Ladisch and colleagues (Purdue University) and is
summarized in Table I.1. “Wet” woodchips, which are unprocessed as provided
by the forestry-products industry as by-products, were used in the analyses. They

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0 Liquid Transportation Fuels from Coal and Biomass
TABLE I.1 Composition of Poplar Woodchips and High-Sugar/Glucan Biomass
(percentage)
Poplar Woodchips HGBM
Acetic acid 01.95 01.08
Ash 00.60 00.33
Cellullose 23.70 25.00
Extractives 01.95 01.08
Lignin 15.75 10.00
Water 18.00 50.00
Xylan 08.06 12.50
contain about 48 percent water, and the concentrations of sugars and lignin are
61 and 30 percent wt/wt, respectively, on a dry-weight basis. Because a high lignin
content is not typical of all cellulosic biomass, the panel generated a “high-sugar/
glucan biomass” (HGBM) feedstock to analyze the effects of a different biomass
composition. HGBM has sugar and lignin concentrations of 75 and 20 percent,
respectively. All other components were kept at the same relative percentages as in
the poplar woodchips; water content was set at 50 percent (instead of the 48 per-
cent in poplar) for simplicity.
Cellulosic-Biomass Feedstock Alternatives
The composition of the feedstock used in the analyses could affect capital and
operating costs. For example, a biorefinery that uses poplar woodchips as a feed-
stock has to include a burner and a steam electrical generator to burn the lignin
residue for electricity generation; in contrast, wheat straw does not have enough
lignin to provide any energy for the biorefinery. Therefore, the panel also assessed
the process economics and environmental effects of biorefineries using different
feedstocks. The different biomass compositions are shown in Table I.2. All com-
positions, apart from the case of poplar, are on a dry-weight basis. References
obtained for these biomass compositions were inconsistent and had large ranges.
The ranges of values overlap for some individual components, such as glucan or
lignin. The most consistent and credible values were selected for the analysis, and
they were mostly averages of the maximum and minimum for the spreads. The
problem of mass closure was resolved by including a trace amount of water to
reach 100 percent, and the price basis for the biomass was adjusted to reflect that.
For example, if the initial price was $70/ton—(2)($35/ton of poplar woodchips on

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Appendix I
TABLE I.2 Composition of Different Feedstocks (percentage)
Poplar Wheat Dry Dry
Woodchips Straw Dry Switchgrass Corn Stover Miscanthus
Acetic acid 1.9 0.0 0.3 0.0 0.0
Ash 0.6 6.4 6.0 7.0 2.0
Cellulose 23.7 39.3 32.2 35.0 38.2
Extractives 1.9 4.2 13.6 5.0 6.9
Lignin 15.7 14.5 17.3 18.5 25.0
Water 48.0 5.0 0.0 2.5 3.6
Xylan 8.1 30.6 27.9 28.0 24.3
Glucose — 0.0% 2.7% 4.0%
a wet-weight basis)—a 2 percent water content would reduce the price to ($70/
ton)(0.98) = $68.60/ton. Another alternative would have been to augment every
percentage composition proportionally so that the sum reached 100 percent. The
two approaches have the same effect, but the former is more efficient.
ETHANOL-BIOREFINERY SIMULATION MODELS
Model for Corn-Grain-to-Ethanol Plants
The corn-grain-to-ethanol process is well developed and understood and is used
by 130–150 ethanol plants in the United States alone; hence, it is a good starting
point to evaluate the modeling method with SuperPro Designer. Because a previ-
ous study analyzed the corn-to-ethanol process with SuperPro Designer (Kwiat-
kowski et al., 2005), it was thought best to remodel the process with the panel’s
simplification constraints (discussed in Chapter 3) and any price changes in cost-
ing and to compare the results with those of the prior study. The panel’s initial
model would not only validate the approach but also verify that it calculated all
the mass balances correctly and performed consistent energy-balance calculations
for the process.
Figure I.1 shows a simple schematic of the corn-grain-to-ethanol manufac-
turing process, and Figure I.2 shows the corresponding schematic in SuperPro
Designer. For adequate separation of concerns, the process was divided into
three sections: preprocessing, production (fermentation), and recovery, including

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Liquid Transportation Fuels from Coal and Biomass
Milling Hydrolysis Fermentation Product
Separation
Fermented
Ethanol
Mash Mash
Meal
Corn,
Wheat Coproducts
Enzymes Yeast
FIGURE I.1 Schematic of processing steps for converting corn to ethanol.
Source: Schwietzke et al., 2008. Reprinted with permission from IEA Bioenergy.
recovery of ethanol as the major product, distillers dry grain solids (DGGS) as a
by-product, and water (hot condensate and backset1). The economic evaluation I-1
ALTF Appendix
report generated by SuperPro Designer is shown at the bottom of Figure I.2.
Cellulosic-Plant Model
Process Overview
There are a lot of similarities between the cellulosic-ethanol and dry-grind corn-
ethanol manufacturing processes, and they share at least five main basic unit oper-
ations (Figure I.3): size reduction, saccharification, fermentation, distillation, and
solids separation (centrifugation). In some plant configurations, saccharification
is attempted simultaneously with fermentation, but such a design is independent
of whether corn or cellulosic biomass is used as feedstock, so it is not treated as a
difference between the two processes. Both systems also need some form of solids
feedstock handling and storage. A variety of alternatives can be used for feedstock
handling; the simplest, and the one modeled in this analysis, is a single storage
bin.
One important difference between the two ethanol-manufacturing alterna-
tives lies in the initial pretreatment of the feedstock after size reduction (grinding
or chopping) for the mash to be saccharified and fermented in the later steps. Dif-
ferent pretreatments are used because of the difference in resilience with respect
1Backset is a portion of thin stillage.

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Appendix I
to “liquefaction” or “softening” of the feedstock. In the case of the cellulosic-bio-
mass process, there are a options to pretreat the lignocellulosic material to make
the glucan and xylan or arabinan fibers available for enzyme degradation into
monomers in the saccharification step.
A second difference has to do with the by-products of the process. More
work and energy are used in the dry-grind corn-based case to produce DGGS of
adequate quality, requiring both an evaporator and a drying step. In the case of
the cellulosic alternative, only a dryer is needed to retrieve the residual solids—
rich in lignin—that are then burned in a boiler to meet the energy requirements
of the biorefinery. Some designs, such as that in the study of Aden et al. (2002),
avoid this drying step and therefore reduce the capital cost further. However, that
type of plant would depend more heavily on external sources of energy for the
plant’s heating and electricity needs.
A third difference is the inclusion of a lignin-based burner and boiler for the
generation of steam and a steam turbine for the generation of electricity in a cellu-
losic-ethanol biorefinery. Those are included in the design to take advantage of the
relatively high content of lignin in the feedstock and the ease with which the lignin
in the residual solids can be combusted by simply providing air. The energy in the
lignin is about 11.5 kbtu/lb (26.7 kJ/g).
In summary, the panel’s simulation model for a cellulosic biorefinery has 10
major unit operations. They are basic and well-characterized units and modeled as
shown in the SuperPro Designer schematic for the plant (Figure I.3). Even if all the
units vary in their complexity (for example, a typical distillation unit includes a
beer column, a rectifier column, a molecular sieve, and a stripper column), for the
sake of simplicity they can be treated as simple “black boxes” that are connected
to each other by one or two streams. Each unit operation is treated as a single
model unit with all its details encapsulated by the single-unit “box,” so that, for
example, in the distillation operation, instead of six units having to be resized with
all the required heat exchangers and other components, only one unit is given the
value of the whole set and resized. Included are also the few heat exchangers out-
side the units that were difficult to model otherwise and that seem to be present in
most of the currently explored configurations both in the literature and in discus-
sions with industry. SuperPro Designer probably models some units—such as the
centrifuge, the fermentor and reaction bins, and the drum dryer—after the actual
physical units. The biggest simplifications are the burner, the steam turbine, and
the propagation system; the first two are modeled as simple generic reaction or
separation boxes. The third is modeled as a single seed fermentor. In reality, it is a

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Appendix I
Economic Evaluation Report March 31, 2008
for
1. EXECUTIVE SUMMARY (2008 prices)
Total Capital Investment 90,886,000 $
Capital Investment Charged to This Project 90,886,000 $
Operating Cost 69,258,000 $/yr
Production Rate 119,902,339.77 kg MP/yr
Unit Production Cost 0.58 $/kg MP
Total Revenues 81,532,000 $/yr
Gross Margin 15.05 %
Return On Investment 18.28 %
Payback Time 5.47 years
IRR (After Taxes) 11.95 %
NPV (at 5.0% Interest) 62,871,000 $
MP = Flow of Component Ethyl Alcohol in Stream
100% EtOH
FIGURE I.2 Continued
system of many seed-fermentor units and cleaning and sterilization systems. That
level of detail is encapsulated in the current unit, which, in essence, is used only
for overall cost-estimation purposes.
SuperPro Designer® Network Model Description
The process is modeled in SuperPro Designer® as a batch process of 19 unit opera-
tions (including heat exchangers and flow splitters and mixers) in which some
units run in continuous mode (see Figure I.4). The longest process, and therefore
the one that defines the length of each batch, is fermentation, which takes 72 h.
The size of the fermentors was set at 800,000 gal for all scenarios, and there can
be anywhere from 5 to 23 fermentor units. The fermentors can run in a staggered
fashion so that the average time to fill them and to empty the ones that have com-
pleted their fermentation is 4 h for the entire set. Thus, the whole process takes
80 h (4 h + 72 h + 4 h).
With respect to the overall batch process, it might be optimistic to consider
the possibility of only 4 h in the front and back ends of the staggered fermenta-

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Liquid Transportation Fuels from Coal and Biomass
Backset
Enzyme
Cellulase, Hemicellulase, etc. Ethanol 8
Water Yeast
1
Lignocellulosic
Liquid 5
Biomass
Steam Steam
Centrifugation
Water 7
2 3 4 Distillation Solids
Pretreatment Saccharification Fermentation & Drying
Residual
6
Solids
FIGURE I.3 Simple schematic of cellulosic-ethanol manufacturing process.
Courtesy of M. Ladisch and colleagues (Purdue University).
tions in the case of 23 fermentors. However, there are only two cases in which
many fermentors were used. For the sake of comparison of different batch ppendix I-3
ALTF A
effi-
ciencies and sizes, the overall time was set at 80 h for all cases. Given the assump-
tions that the plant produces all year and that each batch takes 80 h, 109 batches
could be processed per year. That number was used for all scenario analyses.
It is important to note that many unit operations in the process network
have been considered to operate continuously rather than in a batched mode. The
reason is that apart from the first batch, in which the completion of fermentation
is the step that delays the beginning of other processes—such as distillation and
drying—all the batches allow the processes to be aligned. The products of previ-
ous fermentations are fed into downstream processes in the network, so they never
need to be stopped. The same is true of processes before fermentation, such as
size reduction and shredding. After the first batch—for which shredding must take
place before preprocessing—each batch can be shredded while the preceding batch
is being processed. In this way, all units for continuous processes are sized accord-
ing to their volumetric throughput per batch, assuming a run time of 80 h/batch.
The processing units that have been set as continuous in the network are storage,
the shredder, distillation, centrifugation, the drum dryer, the burner, the steam-
turbine generator, and all mixers, splitters, and heat exchangers.
In contrast, reactor-vessel procedures, such as preprocessing and saccharifica-
tion, could not be resized according to their shorter processing time with respect
to fermentation. In theory, because the processing time for those steps is shorter

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Liquid Transportation Fuels from Coal and Biomass
than that for fermentation, it would be possible to have smaller vessels that are
used more times for each batch while products are stored until the appropriate
volume for the next fermentation is reached. The panel decided, however, to avoid
the use of smaller vessels and, in essence, to use the reactor vessels themselves as
the storage vessels for two reasons. First, it is usually not advisable to leave the
saccharification mash idle in storage for any extended period, because the mix
could spoil and create difficulties for later fermentation. Second, it is unclear
whether having additional storage bins for the different pretreated or saccharified
mixtures would result in substantial cost savings.
As can be seen in Figure I.3 for the case of poplar woodchips as lignocel-
lulosic feedstock, the woodchips are deposited into a solids bin that is just big
enough to hold the biomass required for each batch. The feedstock is passed
through a grinder-shredder that works full-time and then is mixed with water
to reach an approximate solids loading of 30 percent. After being heated by a
heat-exchange element with the output stream of this step, the mixture is fed into
the pretreatment vessel with the hot thin stillage backset. Of the many possible
options, the pretreatment chosen for this model is the hot-water method in which
the mash—now with a 21 percent solids loading after mixing with the backset—is
heated with steam to 200°C for 5 min.
After pretreatment, the mash is transferred into a new reaction vessel, where
it is cooled down to 65°C and mixed with cellulases at 12.6 percent wt/wt glucan.
The mix is stirred for 36 h to achieve about 80–90 percent sugar yields from the
total cellulose and hemicellulose in the biomass. Once that stage is complete, the
mix is transferred into the fermentor, where it is cooled to 32°C and mixed with
yeast at a concentration of 0.125 percent wt/wt fermentable sugars. As mentioned
before, 72 h is allowed for fermentation in which 80–90 percent of the available
fermentable sugar is converted into ethanol. The resulting mixture, which contains
about 4–8 percent ethanol, is then passed through the distillation system. The dis-
tillation system is modeled by a single column with the assumption that 99.99 per-
cent of the ethanol can be recovered in the distillate. In this design, the fermented
mixture distilland is heated as much as possible before entering the distillation sys-
tem by heat exchange with both the bottoms stream and the residual liquid stream
not used as backset and by the evaporated water stream from the drying step. This
approach saves as much heat energy as possible for the model.
The bottoms stream, cooled after exchanging heat with the distillation input
stream, is then passed through the centrifuge. For this step, the distribution of
compounds between the water stream and the solids stream is set as a percent-

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Appendix I
age distribution as indicated by Ladish and colleagues, Purdue University. Fifty
percent of the liquid stream, called thin stillage, is recycled as backset to be mixed
with the ground or shredded feedstock for the next batch. The other 50 percent is
treated as the residual liquid stream and for the model’s purposes disposed of and
not included in this analysis. In a real setting, that liquid stream would most likely
be recovered via a water-purification system.
The residual solids coming out of the centrifuge are dried in a drum dryer to
about 15 percent water content with 242°C high-pressure steam as the source of
heat to allow better burning. Once dried, the solids are fed into a burner or boiler
and completely burned in air to CO2 and water. It is assumed that all compounds
other than the ash already in the solids residue are hydrocarbons and are fully
reacted with oxygen to CO2 and water. Nonetheless, in the reaction enthalpy cal-
culations, only lignin is assumed to release heat of reaction. The other compounds
are not included but contribute slightly as a heat sink because they (or their prod-
ucts) have to be heated to the final exhaust temperature. For the sake of simplicity
and because of some particularities of the program, the water to be heated to the
final steam temperature used throughout the plant is mixed with the solids to be
burned even though in reality these would be in separate chambers.
The generated steam is then passed through a steam turbine to generate elec-
tricity. This unit operation, however, could not be modeled adequately, because it
was unclear whether and how it would be possible in the SuperPro Designer pro-
gram to deduct the steam needs of the plant from the steam output of the boiler.
If all generated steam were available for this unit, it would be generating at least
twice the electricity that would be available to the real plant. This unit, nonethe-
less, was used for separating the real steam generated from the CO2 and water
stream resulting from the residual solids burn and was also used to cost the steam
turbine. That was achieved after further calculations to find the real available
steam for electrical-power output—and therefore the size of the unit—were carried
out separately in an Excel spreadsheet.
Plant Cost Calculations
A sample detailed cost analysis for the “base-case” cellulosic plant (poplar feed-
stock and medium case-performance assumptions) is shown in Box I.1 at the end
of this appendix.

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0 Liquid Transportation Fuels from Coal and Biomass
Equipment
With respect to the major equipment specifications and freight on board (FOB)
costs, there is only one unit of every unit operation (or stage)—except perhaps for
one or two heat-exchanger stages that were doubled under some circumstances—
in which the maximum size specifications for a unit were below the through-
put for a particular case. Notable exceptions are the vessels for pretreatment,
saccharificaton, and fermentation, which have constraints on how large they can
be made. Therefore, although costs of all other equipment increase with size to
the power of 0.6–0.7, the equipment for those three stages correlates linearly with
the number of units required. The maximum and therefore the chosen working
size of each vessel was selected by virtue of consolidating the decisions of industry
on sizing vessels, after talks with representatives in charge of these projects, with
the maximum possible size of 1 million gallons reported in the Aden et al. (2002)
study. The current estimate of the base cost of these vessels was also validated in
those talks.
As mentioned before, the single distillation column is a proxy for a more
detailed distillation unit that to a good approximation follows single-unit com-
parison with Schwietzke et al.’s model (2008). The actual distillation stage would
include a beer column, a rectifier column, a molecular sieve, and a stripper col-
umn, but the value and the behavior of this set of components were appropriately
emulated by the single column modeled in this analysis. The overall cost of this
stage was also validated by talks with industry and by the costs of such units as
the centrifuge and the dryer. Scaling exponent values were also fine-tuned after
discussions with industry. The scaling exponent value varies: distillation grows
approximately with a scaling exponent of 0.55, and the centrifuge with 0.8. The
default value was taken as 0.7.
Although the burner or boiler and steam-turbine generator help to create a
more efficient biorefinery from an energy point of view, it is not obvious whether
this is the most economical choice relative to the use of natural gas or coal for the
energy needs of the plant. They have been included here to minimize reliance on
fossil fuels. The sum of the costs of the boiler and turbine was validated indepen-
dently and, on the basis of usual estimates, is 40–50 percent of total equipment
costs. It varied from case to case, however, because the turbine cost for different
cases was re-estimated according to the amount of available steam for electricity
generation.

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Appendix I
It should be noted that the FOB cost of equipment is about 25 percent of
the total plant cost. In addition to the costs of the basic units, adding such items
as piping, instrumentation, insulation, electrical facilities, buildings, and “yard
improvement” (here taken as the initial landscaping needed for the construction of
the facility) increases the cost. All those values are taken as percentages of the cost
of the units and have been validated with industry. In addition, the percentage cost
of engineering and construction and the contractor’s fee and contingency have to
be included. The sum is the total “direct fixed capital cost” (DFC). Finally, there
are the startup costs and the initial working capital, which are expressed as per-
centages of the DFC (in Section 10A of the SuperPro Designer Economic Analysis
Report Sample). Royalty fees, fixed at about $4 million and not based directly on
the DFC, still need to be added to the DFC to provide the figure for total capital
investment.
REFERENCES
Aden, A., M. Ruth, K. Ibsen, J. Jechura, K. Neeves, J. Sheehan, B. Wallace, L. Montague,
A. Slayton, and J. Lukas. 2002. Lignocellulosic Biomass to Ethanol Process Design and
Economics Utilizing Co-Current Dilute Acid Prehydrolysis and Enzymatic Hydrolysis
for Corn Stover. Golden, Colo.: National Renewable Energy Laboratory.
Kwiatkowski, J., A.J. McAllon, F. Taylor, and D.B. Johnston. 2005. Modeling the process
and costs of fuel ethanol production by the corn dry-grind process. Industrial Crops
and Products 23:288-296.
Schwietzke, S., M.R. Ladisch, L. Russo, K. Kwant, T. Makinen, B. Kavalov, K. Maniatis,
R. Zwart, G. Shahanan, K. Sipila, P. Grabowski, B. Telenius, M. White, and A. Brown.
2008. Gaps in the research of 2nd generation transportation biofuels. IEA Bioenergy
T41:2008:2001.